Instructions to use MSLars/nonsense-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MSLars/nonsense-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MSLars/nonsense-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MSLars/nonsense-detection") model = AutoModelForTokenClassification.from_pretrained("MSLars/nonsense-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MSLars/nonsense-detection: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/MSLars/nonsense-detection/resolve/main/training_args.bin
- Command line
-
hf download hf://MSLars/nonsense-detection/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MSLars/nonsense-detection/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- ad05fe79b0606ab193f488d241fb32fa1d58dc75fe360798b66694ece8e693fb
- Size of remote file:
- 5.5 kB
- SHA256:
- 3ca518c853df70655636d7135e6eb0baef0f2077c10263be20b7dd1da902e8a0
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